MilaNLProc/survey-language-technologies huggingface dataset:
Gender: Male 
Age: 18-24
Nationality: United States
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Listen to hiphop and rap;Exercise;Use social media 
Devices used daily: Laptop;Tablet;Smartwatch;Smartphone 
NLP tools known: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Google Gemini 
LLM use cases: Translation;Writing (e.g., composing emails);Paraphrasing or finding synonyms 
Contexts of LLM use: Entertainment;Personal;Work 
Prompt 1: when will isreal war end
Prompt 2: what will be outcome of the executive orders trump signed
Prompt 3: best hotel in greenville
Prompt 4: effects of abortion in teenagers
Prompt 5: time in uk now
Prompt 6: best hotel in parma italy
Prompt 7: about maldives
Prompt 8: live in dubai
Prompt 9: common dishes in dubai
Prompt 10: flight time from chicago to uk
Gender: Male 
Age: 55-60
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Not employed and not looking for work
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Use social media;Attend football matches;Watch sports 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Learning (e.g., explaining complex concepts in simple terms);Get information about current events;Answering questions about general knowledge 
Contexts of LLM use: Entertainment;Personal 
Prompt 1: History of the premier League
Prompt 2: Tell me about Donald Trump
Prompt 3: India v England Cricket History
Prompt 4: Best films in the Oscars
Prompt 5: Storms in the UK
Prompt 6: Why has it snowed in Florida
Gender: Male 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Use social media;Exercise;Watch sports;Go to gigs;Attend football matches 
Devices used daily: Smartphone;Laptop;Smartwatch 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Google Gemini;Grok 
LLM use cases: Translation;Generic chatbot conversation;Paraphrasing or finding synonyms;Analyze data;Get information about current events;Answering questions about general knowledge;Collecting references;Summarizing long texts 
Contexts of LLM use: Work;School/University;Personal;Learning 
Prompt 1: what is americas population
Prompt 2: how many states did donald trump win in the us election
Prompt 3: what is the interest rate of us going to be in the next 6 months
Prompt 4: unemployment rate in the us 2025
Prompt 5: forensic sebiome analysis
Prompt 6: fpl fixtures
Gender: Male 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Undergraduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Listen to classical music;Exercise;Use social media;Watch sports;Do arts and crafts 
Devices used daily: Laptop;Smartphone 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Meta Llama 2;Perplexity 
LLM use cases: Writing (e.g., composing emails);Paraphrasing or finding synonyms;Brainstorming;Analyze data;Completing assignments;Solving math or logical problems 
Contexts of LLM use: Work;Learning;Personal;Creative or artistic 
Prompt 1: what is the benefit of bitcoin halving
Prompt 2: write about hinkal
Prompt 3: give me a mind blowing write-up on intuition
Prompt 4: write a proposal on Single Cell protein
Prompt 5: write a letter of recommendation to the embassy
Prompt 6: type SOP FOR ME
Gender: Male 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to hiphop and rap;Use social media;Do arts and crafts 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Spell checker (i.e., correcting misspellings) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Grok;Google Bard;Meta Llama 2 
LLM use cases: Brainstorming;Writing (e.g., composing emails);Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge 
Contexts of LLM use: Work;Personal;Learning 
Prompt 1: Can weather changes lead to earth degradation
Prompt 2: What is the best way to make oats
Prompt 3: Which is the smallest mountain in the world
Prompt 4: How do someone exfoliate
Prompt 5: Do hybrid cars last as long as gasoline cars
Prompt 6: What is the capital of Malta
Prompt 7: Which is the most popular way of cooking rice
Prompt 8: Can bacteria infections give rise to other infections
Prompt 9: What is the meaning of Bachelorette
Prompt 10: Which is the smallest country in the world
Comments: No
Gender: Female 
Age: 18-24
Nationality: United Kingdom
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Rent 
Employment: Not employed and not looking for work
Occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products);Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Homemaker
Hobbies: Listen to classical music;Exercise;Use social media;Listen to rock/indie music 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Never
Comments: No
Gender: Male 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Employed full time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Watch sports;Use social media 
Devices used daily: Smartphone;Laptop 
NLP tools known: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Google Gemini 
LLM use cases: Brainstorming;Answering questions about general knowledge;Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: Work;Entertainment;Technical;Learning;Personal 
Prompt 1: What is the shape of the earth
Prompt 2: Could you tell me the richest actor in hollywood
Prompt 3: How does a refrigerator achieve its cooling
Prompt 4: When is the best time for a child to start schooling
Prompt 5: How are coral beads made
Gender: Male 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Do arts and crafts IT technician
Devices used daily: Laptop;Smartphone 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Grammar checker (i.e., correcting grammar mistakes);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Google Gemini;GitHub Copilot;Jasper;Microsoft Bing AI;Pi 
LLM use cases: Coding;Analyze data;Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: Technical;Work 
Prompt 1: How can I improve the performance of this Python script that processes a large JSON file?
Prompt 2: How do I resolve the Cannot find module error when running a TypeScript app?
Prompt 3: How do I integrate Stripe payments into a React app?
Prompt 4: What are the key principles of writing maintainable and scalable code?
Prompt 5: Can you explain the difference between quicksort and mergesort with examples
Prompt 6: What are the best practices for using Docker with a Node.js application?
Prompt 7: How do I resolve the Cannot find module error when running a TypeScript app
Prompt 8: What are the best practices for designing RESTful APIs, and how do I structure endpoints effectively?
Prompt 9: Why am I getting a CORS error when making an API request from my frontend application?
Prompt 10: How do I set up Webpack for a React project, and what are the key configuration files?
Comments: The survey is good and i appreciate for the opportunity to participate.
Gender: Male 
Age: 55-60
Nationality: United States
Ethnicity: Black or African American No.
Marital status: Married No.
First language: English No.
Religion: Christian No.
Education: Undergraduate degree
Mother's education: Doctorate or above
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 6
Home: Own No.
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Exercise;Listen to hiphop and rap;Watch sports;Attend football matches;Other (Please specify) NBA
Devices used daily: Smartphone;Laptop No.
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) No.
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) No.
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) No.
Frequency of LLM use: Every day
LLMs used: ChatGPT;Google Gemini;Meta Llama 2;Snapchat My AI;Microsoft Bing AI;Claude;Character.AI No.
LLM use cases: Coding;Brainstorming;Writing (e.g., composing emails);Solving math or logical problems;Analyze data;Completing assignments;Summarizing long texts No.
Contexts of LLM use: School/University;Work;Personal No.
Prompt 1: What is matter?
Prompt 2: Please indicate whether you agree or disagree with the following statement: "The federal minimum wage should be increased from $7.25 to $17 over a five-year period." Agree or disagree.
Prompt 3: Tatyana knew that Grandma always enjoyed serving an abundance of food to her guests. Who does the "her" in the above passage refer to?
Prompt 4: What does 1% portion of $1000 equal to?
Prompt 5: What does a 1% portion of -$1000 equal to?
Prompt 6: How much do you value the 1% portion of $1000?
Prompt 7: How much do you value the 1% portion of -$1000?
Prompt 8: Which city’s metro system has the largest number of stations?
Prompt 9: What was the price of a barrel of oil in February 2020?
Prompt 10: Can you briefly explain why you chose this rating?
Comments:  AI chatbots are powerful tools for gathering information and providing assistance efficiently.
Gender: Female 
Age: 35-44
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: Doctorate or above
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Hobbies: Attend football matches 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Character.AI 
LLM use cases: Writing (e.g., composing emails);Paraphrasing or finding synonyms;Solving math or logical problems 
Contexts of LLM use: Entertainment;School/University;Learning;Work 
Prompt 1: what is 1000 x 19.5
Gender: Female 
Age: 35-44
Nationality: United Kingdom;Kenya
Ethnicity: Black or African American 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Prefer not to say
Hobbies: Go to gigs;Listen to hiphop and rap;Exercise;Do arts and crafts;Go to museums and galleries 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Spell checker (i.e., correcting misspellings);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Snapchat My AI;Character.AI 
LLM use cases: Translation;Brainstorming;Writing (e.g., composing emails);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Digital content creation (e.g., creation of social media content) 
Contexts of LLM use: Work;School/University;Learning;Personal;Creative or artistic 
Prompt 1: Should i marry for money
Prompt 2: application for customer job skills
Prompt 3: how to lose weight
Prompt 4: I want to be a rich house wife
Prompt 5: Is it true you can marry for money and fall in love later
Prompt 6: how to write cover lwtters
Prompt 7: how do i deal with my mental health
Prompt 8: marriage life
Prompt 9: why are divorce cases so high
Prompt 10: I still love my ex
Comments: no
Gender: Female 
Age: 55-60
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 5
Home: Own 
Employment: Stay-at-home spouse or partner
Occupation: Homemaker
Mother's occupation: Homemaker
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Exercise;Do arts and crafts 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Rarely
Prompt 1: tell me something 
Prompt 2: what time of day is it
Prompt 3: are you ok
Prompt 4: what is the weather
Prompt 5: what is courage
Prompt 6: favourite colour
Prompt 7: how to make
Prompt 8: favourite movie
Prompt 9: favourite thing
Prompt 10: how to find
Gender: Male 
Age: 55-60
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Exercise;Watch sports;Use social media 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails);Get information about current events;Answering questions about general knowledge 
Prompt 1: why is my circulation so bad?
Prompt 2: how would i set up an automated trading bot for scalping the betfair trading exchange?
Prompt 3: please details a specific football trading strategy that is profitable
Prompt 4: what loopholes are there when using the betfair  sports exchanges to make a guaranteed profit?
Prompt 5: when retired what is the best way to switch mindset from being a saver to a spender?
Prompt 6: can you still build muscle in your 50's?
Prompt 7: what tax considerations are there when moving to spain?
Prompt 8: how do you become a resident of Spain?
Prompt 9: how much money do you need to become a permanent resident of Spain?
Prompt 10: if i have paid enough National Insurance do I still have to pay national insurance if i retire before my state pension age?
Gender: Male No.
Age: 18-24
Nationality: United States
Ethnicity: Black or African American No.
Marital status: Single No.
First language: English No.
Religion: Christian No.
Education: Undergraduate degree
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Own No.
Employment: Employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to hiphop and rap;Watch sports;Other (Please specify) NBA.
Devices used daily: Smartphone;Laptop;Smartwatch No.
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) No.
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) No.
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) No.
Frequency of LLM use: Every day
LLMs used: ChatGPT;Character.AI;Google Gemini;Meta Llama 2 No.
LLM use cases: Coding;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Writing (e.g., composing emails);Brainstorming;Solving math or logical problems No.
Contexts of LLM use: School/University;Work;Learning No.
Prompt 1: Can you summarize the key findings of the latest IPCC report on climate change?
Prompt 2: Can you write a short story about a robot who learns to appreciate the beauty of nature?
Prompt 3: Translate the following sentence into Spanish: "The quick brown fox jumps over the lazy dog."
Prompt 4: What are the main differences between capitalism and socialism?
Prompt 5: Can you provide me with a list of 10 healthy dinner recipes?
Prompt 6: Explain the concept of artificial intelligence in simple terms.
Prompt 7: Write a poem about the ocean.
Prompt 8: What are the top 10 tourist attractions in Paris?
Prompt 9: Can you help me write a persuasive essay on the importance of recycling?
Prompt 10: What are the side effects of drinking too much coffee?
Comments: AI chatbots are highly effective for collecting information and offering support quickly and efficiently.
Gender: Female 
Age: 18-24
Nationality: United States
Ethnicity: Black or African American 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Undergraduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 4
Home: Own 
Employment: Employed part time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Listen to hiphop and rap;Exercise;Use social media;Go to museums and galleries 
Devices used daily: Smartwatch;Laptop;Smartphone 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Meta Llama 2;Perplexity 
LLM use cases: Brainstorming;Writing (e.g., composing emails);Digital content creation (e.g., creation of social media content);Generic chatbot conversation;Completing assignments 
Contexts of LLM use: Personal;Entertainment;Learning;Work;Creative or artistic 
Prompt 1: Generate a list of 10 fun questions for a game night.
Prompt 2: Tell me a joke about robots and humans.
Prompt 3: Describe a futuristic city in 100 years.
Prompt 4: Invent a new holiday and explain how people celebrate it.
Prompt 5: What would a conversation between a cat and a dog sound like?
Prompt 6: Create a smoothie recipe that’s both tasty and nutritious
Prompt 7: What are some creative uses for leftover rice?
Gender: Female 
Age: 60+
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Self-employed part time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Armed forces occupations (includes all jobs held by members of the armed forces)
Hobbies: Listen to rock/indie music;Go to gigs;Exercise;Use social media 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Never
Gender: Female 
Age: 35-44
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Use social media;Exercise 
Devices used daily: Laptop;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Rarely
LLMs used: None of these 
LLM use cases: Writing (e.g., composing emails) 
Contexts of LLM use: Other (specify) for a survey task
Gender: Female 
Age: 25-34
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 7
Home: Rent 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Use social media;Exercise;Attend football matches 
Devices used daily: Laptop;Tablet;Smartphone 
NLP tools known: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Spell checker (i.e., correcting misspellings) 
NLP tools used: Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Every day
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge 
Contexts of LLM use: Work;Learning 
Prompt 1: How far is Dallas from Arkansas, give an estimate
Prompt 2: Give me a recipe for pancakes
Prompt 3: Please, how do I locate the nearest hospital in South Carolina
Prompt 4: What is the title of this movie
Prompt 5: What color of cap is this